The temporal encoding is to represent the temporal information of each node in the substructure node set. Instead of the absolute encoding in [1]}, we consider a relative encoding for dynamic graphs. Concretely, for each node in the substructure node set \(v_j^i \in \mathcal {S}^i(e^t_{tgt})\) , the data source for relative time encoding is defined as the difference between the occurring time \(t\)  of target edge and the current time of timestamp \(i\) . The motivation behind this is that our main task is to predict the legality of the target edge, so the relative time to the target edge is a more significant factor for anomaly detection. Similar linear mapping is also applied as the encoding function, and the formal expression of relative temporal encoding is given as
\(\mathbf {x}_{temp}(v_j^i)= linear(\Vert t-i\Vert ) \in \mathbb {R}^{d_{enc}},\) 
